Optimal design method of public transit network considering transfer efficiency
Abstract Improving the sharing rate of public transport and reducing operation costs are key factors affecting the sustainable development of the public transport system. After quantifying the impact of transfer, this study proposes a multi‐objective optimization model of bus networks considering th...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Wiley
2023-06-01
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Series: | IET Intelligent Transport Systems |
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Online Access: | https://doi.org/10.1049/itr2.12349 |
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author | Dian Jing Enjian Yao Rongsheng Chen Xun Sun |
author_facet | Dian Jing Enjian Yao Rongsheng Chen Xun Sun |
author_sort | Dian Jing |
collection | DOAJ |
description | Abstract Improving the sharing rate of public transport and reducing operation costs are key factors affecting the sustainable development of the public transport system. After quantifying the impact of transfer, this study proposes a multi‐objective optimization model of bus networks considering the integral transfer efficiency and operation costs, whose optimal solution is hard to find. Since the heuristic algorithm has great global searchability, a non‐dominated sorted genetic algorithm (NSGA‐II) is adopted to solve this NP‐hard problem. Also, an adaptive mutation mode selection algorithm is proposed to enhance the solution efficiency. The optimization framework is applied to the benchmark case of the Swiss public transit network. The results show that the method significantly improves the transfer efficiency of the designed network when compared to existing studies. After calculation, it is found that enhancing the direct rate can improve transfer efficiency, but with high costs. Moreover, the proposed method can design an efficient and economic network to balance the benefits of passengers and operators in practice. |
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id | doaj.art-cb1f687862dd4cc2b1e5d88b6ea263a1 |
institution | Directory Open Access Journal |
issn | 1751-956X 1751-9578 |
language | English |
last_indexed | 2024-03-13T05:06:13Z |
publishDate | 2023-06-01 |
publisher | Wiley |
record_format | Article |
series | IET Intelligent Transport Systems |
spelling | doaj.art-cb1f687862dd4cc2b1e5d88b6ea263a12023-06-16T15:37:35ZengWileyIET Intelligent Transport Systems1751-956X1751-95782023-06-011761118113610.1049/itr2.12349Optimal design method of public transit network considering transfer efficiencyDian Jing0Enjian Yao1Rongsheng Chen2Xun Sun3Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing People's Republic of ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing People's Republic of ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing People's Republic of ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing People's Republic of ChinaAbstract Improving the sharing rate of public transport and reducing operation costs are key factors affecting the sustainable development of the public transport system. After quantifying the impact of transfer, this study proposes a multi‐objective optimization model of bus networks considering the integral transfer efficiency and operation costs, whose optimal solution is hard to find. Since the heuristic algorithm has great global searchability, a non‐dominated sorted genetic algorithm (NSGA‐II) is adopted to solve this NP‐hard problem. Also, an adaptive mutation mode selection algorithm is proposed to enhance the solution efficiency. The optimization framework is applied to the benchmark case of the Swiss public transit network. The results show that the method significantly improves the transfer efficiency of the designed network when compared to existing studies. After calculation, it is found that enhancing the direct rate can improve transfer efficiency, but with high costs. Moreover, the proposed method can design an efficient and economic network to balance the benefits of passengers and operators in practice.https://doi.org/10.1049/itr2.12349Mandl's benchmark problemnon‐dominated sorted genetic algorithmtransfer efficiencyurban transit routing problem |
spellingShingle | Dian Jing Enjian Yao Rongsheng Chen Xun Sun Optimal design method of public transit network considering transfer efficiency IET Intelligent Transport Systems Mandl's benchmark problem non‐dominated sorted genetic algorithm transfer efficiency urban transit routing problem |
title | Optimal design method of public transit network considering transfer efficiency |
title_full | Optimal design method of public transit network considering transfer efficiency |
title_fullStr | Optimal design method of public transit network considering transfer efficiency |
title_full_unstemmed | Optimal design method of public transit network considering transfer efficiency |
title_short | Optimal design method of public transit network considering transfer efficiency |
title_sort | optimal design method of public transit network considering transfer efficiency |
topic | Mandl's benchmark problem non‐dominated sorted genetic algorithm transfer efficiency urban transit routing problem |
url | https://doi.org/10.1049/itr2.12349 |
work_keys_str_mv | AT dianjing optimaldesignmethodofpublictransitnetworkconsideringtransferefficiency AT enjianyao optimaldesignmethodofpublictransitnetworkconsideringtransferefficiency AT rongshengchen optimaldesignmethodofpublictransitnetworkconsideringtransferefficiency AT xunsun optimaldesignmethodofpublictransitnetworkconsideringtransferefficiency |